• Proceedings of the KIEE Conference
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• 2003.11a
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• pp.113-115
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• 2003

본 논문에서는 확률적인 전역 최적해 탐색 방식인 유전알고리즘과 경험적인 최적화 알고리즘인 Tabu 탐색법을 이용하여 실시간으로 적용 가능한 배전계통 선로 재구성 및 커패시터 용량결정 방안을 제안하고자 한다. 제안한 알고리즘은 PC Cluster System으로 병렬처리하여 배전계통의 손실 최소화를 위한 선로 재구성 및 커패시터 용량 결정문제의 최적해 탐색에 소요되는 계산시간을 단축하고, 실시간 지원시스템의 성능 개선을 도모하고자 한다. PC Cluster System은 이용자의 편의를 위해서 MS Windows 환경에서 구축하였고, Visual C++ 환경에서 개발하였다. 제안한 방법의 유용성을 입증하기 위해 참고 문헌의 예제 계통에 적용한 후 종래의 방법과 비교함으로써 제안한 방법이 해의 탐색속도 및 해의 성능면에서 우수함을 입증하였다.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.178-192
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• 2021

File system forensics typically focus on the contents or timestamps of a file, and it is common to work around file/directory centers. But to recover a deleted file on the disk or use a carving technique to find and connect partial missing content, the evidence must be analyzed using cluster-centered analysis. Forensics tools such as EnCase, TSK, and X-ways, provide a basic ability to get information about disk clusters, but these are not the core functions of the tools. Alternatively, Sysinternals' DiskView tool provides a more intuitive visualization function, which makes it easier to obtain information around disk clusters. In addition, most current tools are for Windows. There are very few forensic analysis tools for MacOS, and furthermore, cluster analysis tools are very rare. In this paper, we developed a tool named FACT (Forensic Analyzer based Cluster Information Tool) for analyzing the state of clusters in a HFS+ file system, for digital forensics. The FACT consists of three features, a Cluster based analysis, B-tree based analysis, and Directory based analysis. The Cluster based analysis is the main feature, and was basically developed for cluster analysis. The FACT tool's cluster visualization feature plays a central role. The FACT tool was programmed in two programming languages, C/C++ and Python. The core part for analyzing the HFS+ filesystem was programmed in C/C++ and the visualization part is implemented using the Python Tkinter library. The features in this study will evolve into key forensics tools for use in MacOS, and by providing additional GUI capabilities can be very important for cluster-centric forensics analysis.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.445-452
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• 2019

In this study, parallel processing codes of k-means clustering algorithm were developed and implemented in a PC-cluster for unsupervised classification of large satellite images. We implemented intra-node code using multicores of CPU (Central Processing Unit) based on OpenMP (Open Multi-Processing), inter-nodes code using a PC-cluster based on message passing interface, and hybrid code using both. The PC-cluster consists of one master node and eight slave nodes, and each node is equipped with eight multicores. Two operating systems, Microsoft Windows and Canonical Ubuntu, were installed in the PC-cluster in turn and tested to compare parallel processing performance. Two multispectral satellite images were tested, which are a medium-capacity LANDSAT 8 OLI (Operational Land Imager) image and a high-capacity Sentinel 2A image. To evaluate the performance of parallel processing, speedup and efficiency were measured. Overall, the speedup was over N / 2 and the efficiency was over 0.5. From the comparison of the two operating systems, the Ubuntu system showed two to three times faster performance. To confirm that the results of the sequential and parallel processing coincide with the other, the center value of each band and the number of classified pixels were compared, and result images were examined by pixel to pixel comparison. It was found that care should be taken to avoid false sharing of OpenMP in intra-node implementation. To process large satellite images in a PC-cluster, code and hardware should be designed to reduce performance degradation caused by file I / O. Also, it was found that performance can differ depending on the operating system installed in a PC-cluster.

• Journal of Environmental Science International
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• v.12 no.12
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• pp.1215-1225
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• 2003

The purpose of this research was to investigate the characteristics of urban ecotopes and to classify ecotopes systematically from them. Total of 15 characteristics for classification of ecotopes were selected, and there were categorized 3 factors, that is abiotic, biotic and anthropological factors. The ecotope types in the study area were classified into 67. The classification of ecotope was made with SPSS for Windows Version 10.0 on the basis of the 15 characteristics. As the results of cluster analysis using the average linkage method between groups, groups of ecotope type were divided into 15 clusters. It was known that there was not a great difference in an affinity as the result of overlapping the maps of ecotope type and land use type. This research suggested characteristics for classification of ecotopes, but there was a limit to Set the objective method for grade classification because of lacking in the basic data, the research of characteristics will be accomplished continuously.

• Proceedings of the IEEK Conference
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• 2003.11b
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• pp.45-48
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• 2003

We can easily buy network system for high performance micro-processor, progress computer architecture is caused of high bandwidth and low delay time. Coupling PC-based commodity technology with distributed computing methodologies provides an important advance in the development of single-user dedicated systems. Lately Network is joined PC or workstation by computers of high performance and low cost. Than it make intensive that Cluster system is resembled supercomputer. Unix, Linux, BSD, NT(Windows series) can use Cluster system OS(operating system). I'm chosen linux gain low cost, high performance and open technical documentation. This paper is benchmark performance of Beowulf clustering by UltraSPARC-1K(64bit-RISC processor). Benchmark tools use MPI(Message Passing Interface) and NetPIPE. Beowulf is a class of experimental parallel workstations developed to evaluate and characterize the design space of this new operating point in price-performance.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.04a
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• pp.389-392
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• 2002

광선 추적 기법은 컴퓨터를 활용하여 사진과 같은 고해상도의 영상을 얻어내기 위한 렌더링 기법 중 하나이다. 그러나 이 기법은 이미지를 생성할 때 각 접마다 시뮬레이션을 하여 계산해 내므로 접의 수에 따른 계산량이 증가되고 그에 따른 계산 시간이 많이 소요된다는 단점이 있다. 이러한 많은 계산량을 처리하기 위해 병렬처리 기법을 활용할 수 있다. 본 논문에서는 MPI(Message Passing Interface)를 이용한 병렬 광선 추적 기법을 제시하고 그러한 기법을 여러대의 PC를 이용한 PC Clustering 기법에 적용시켜봄으로써 복잡한 계산에 소요되는 시간을 단축시키고자 하였다. 또한 작업의 크기의 변화에 따른 작업 시간과 노드 수의 증가에 따른 속도 향상률을 알아보았다. 이러한 실험을 위해 병렬 프로그래밍 도구로는 Windows NT 기반의 MPICH를 사용하였고 노드의 수는 3대에서 30대까지 증가시켰다. 노드의 수가 증가함에 따라 렌더링에 소요되는 시간이 선형적으로 감소함을 알 수 있었다.

• Bulletin of the Korean Space Science Society
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• 2009.10a
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• pp.29.2-29.2
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• 2009

During the last four years, we have performed Sejong/ARCSEC Ca uvby survey using the CTIO-1m telescope aimed at obtaining Ca uvby photometry for about 50 globular clusters and selected fields in Baade's Windows. Our results show that Ca uvby photometric system can provide a powerful method to probe multiple populations in Galactic globular clusters. We will discuss the multiple stellar population in the globular cluster NGC6218 and NGC6752 as illustrations.

• Journal of the Korean Society of Propulsion Engineers
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• v.11 no.1
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• pp.1-10
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• 2007

Three dimensional structures of detonation waves propagating in a square tube were investigated using a high resolution CFD code coupled with a conservation equation of reaction progress variable and an one-step irreversible reaction. The code were parallelized based on domain decomposition technique using MPI library. The computations were carried on an in-house Windows cluster with AMD processors. Three-dimensional unsteady analysis results in the smoked-foil records caused by the instabilities of the detonation waves, which showed the rectangular and diagonal modes of detonation instabilities depending on the initial condition of disturbances and the spinning detonation for case of small reaction constant.

• Korean Journal of Human Ecology
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• v.19 no.1
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• pp.157-165
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• 2010

The purpose of this study was to investigate the awareness and practices for diet according to the lifestyles of college students in Youngnam region. The data were collected by self-administered questionnaires during May 2007. One hundred-ninety samples were analyzed by SPSS Windows. Frequencies, Cronbach's alpha, factor analysis, cluster analysis, one-way analysis of variance, Duncan's multiple range test and chi-square test were conducted. The results were as follows. Lifestyles were categorized into four factors by factor analysis: popularity-seeking type, body-management-seeking type, convenience-seeking type and healthy-seeking type. In addition, the respondents belonged to one of four groups by cluster analysis: body-management-seeking group, popularity-seeking group, convenience-seeking group, and healthy-seeking group. There were significant differences in perception about individual body images, concern of diet, awareness of diet necessity and knowledge and practices for diet among the four groups. That is, the body-management-seeking group showed the highest levels of concern of diet, awareness of diet necessity and the practice of fasting therapy. Additionally, the healthy-seeking group showed the highest level of practice of exercise therapy.

• Korean Journal of Human Ecology
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• v.20 no.6
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• pp.1135-1151
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• 2011

This study examined green consumption behavior according to the lifestyles of college students. The data were collected from 314 college students in Yeungnam region by a self-administered questionnaire. Frequencies, Cronbach's alpha, factor analysis, cluster analysis, chi-square tests, one-way analysis of variance, Duncan's multiple range tests, Pearson's correlation analysis, and multiple regression analyses were conducted by SPSS Windows V.18.0. According to the result of factor analysis, lifestyles were categorized into six factors: thrift-saving type, enthusiastic activity type, brand ostentation type, freedom-seeking type, material oriented type, and practice-seeking type. Cluster analysis showed respondents belonged to one of four groups: thrift practice group, indifference group, freedom-seeking group, and material ostentation group. The levels of green purchase behavior, green usage behavior and green disposal behavior of the respondents was not high. The thrift practice group showed higher levels of green purchase behavior, green usage behavior, and green disposal behavior. Finally, according to multiple regression analyses, environmental consciousness, knowledge about green consumption, lifestyle groups were the significant factors affecting green consumption behaviors. These results imply that green consumption education for college students should be activated to induce green life.